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High volume bus stop upstream average waiting time for working capacity and quality of service

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  • Jonathan M. Bunker

    (Queensland University of Technology)

Abstract

High volume bus facilities range from on-street facilities to dedicated Bus Rapid Transit (BRT) facilities. The aim of this study is to better understand performance by directly relating critical stop bus capacity to quality of service (QOS), which measures performance from the passengers’ and operator’s perspectives. The US transit capacity and quality of service manual methodology estimates facility bus capacity based on critical stop operation using a failure rate approach. However, this approach is inaccurate under high volume conditions and the failure rate is a difficult measure to prescribe and to interpret. This research provides an improved understanding of operation by instead considering bus upstream average waiting time to measure capacity and QOS performance, because it is experienced directly by passengers and is an indicator of the impact upon general traffic. A fundamental microscopic simulation model is developed with many bus stop operational aspects occurring stochastically, including upstream arrivals. An empirical upstream average waiting time model is calibrated for five bus stop scenarios including BRT and on-street conditions. This is then used to determine working capacity based on QOS threshold upstream average waiting time. Assigning a worse threshold gives diminishing returns in working capacity, particularly for waiting times beyond 60 s. For an assigned threshold, as loading area processing time reduces, working capacity increases more markedly. This demonstrates that BRT stations are more productive than general on-street bus stops. An example shows that a policy decision exists for the operator as to which QOS threshold to accept in balance with working capacity that suits the desired schedule. It is also discussed that the model enables the operator to evaluate the impact of design or operational changes as well as timetable changes on capacity and QOS.

Suggested Citation

  • Jonathan M. Bunker, 2018. "High volume bus stop upstream average waiting time for working capacity and quality of service," Public Transport, Springer, vol. 10(2), pages 311-333, August.
  • Handle: RePEc:spr:pubtra:v:10:y:2018:i:2:d:10.1007_s12469-018-0179-1
    DOI: 10.1007/s12469-018-0179-1
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    References listed on IDEAS

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    1. Alpkokin, Pelin & Ergun, Murat, 2012. "Istanbul Metrobüs: first intercontinental bus rapid transit," Journal of Transport Geography, Elsevier, vol. 24(C), pages 58-66.
    2. Ela Babalik-Sutcliffe & Elif Can Cengiz, 2015. "Bus Rapid Transit System in Istanbul: A Success Story or Flawed Planning Decision?," Transport Reviews, Taylor & Francis Journals, vol. 35(6), pages 792-813, November.
    3. Hidalgo, Dario & Lleras, Germán & Hernández, Enrique, 2013. "Methodology for calculating passenger capacity in bus rapid transit systems: Application to the TransMilenio system in Bogotá, Colombia," Research in Transportation Economics, Elsevier, vol. 39(1), pages 139-142.
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    Cited by:

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    2. Kh Md Nahiduzzaman & Tiziana Campisi & Amin Mohammadpour Shotorbani & Khaled Assi & Kasun Hewage & Rehan Sadiq, 2021. "Influence of Socio-Cultural Attributes on Stigmatizing Public Transport in Saudi Arabia," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    3. Lu Liu & Zhanglei Bian & Qinghui Nie, 2022. "Finding the Optimal Bus-Overtaking Rules for Bus Stops with Two Tandem Berths," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    4. Sewmini Jayatilake & Jonathan M. Bunker & Ashish Bhaskar & Marc Miska, 2021. "Time–space analysis to evaluate cell-based quality of service in bus rapid transit station platforms through passenger-specific area," Public Transport, Springer, vol. 13(2), pages 395-427, June.
    5. Mohammad Sadrani & Ahmad Reza Jafarian-Moghaddam & Mohsen Aboutalebi Esfahani & Amir Masoud Rahimi, 2023. "Designing limited-stop bus services for minimizing operator and user costs under crowding conditions," Public Transport, Springer, vol. 15(1), pages 97-128, March.
    6. Li He & Martin Trépanier & Bruno Agard, 2021. "Space–time classification of public transit smart card users’ activity locations from smart card data," Public Transport, Springer, vol. 13(3), pages 579-595, October.

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    More about this item

    Keywords

    Transit capacity; Transit quality of service; Bus; Passenger; Delay;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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